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The Feasibility of Constraining Dark Energy Using LAMOST Redshift Survey

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Chinese Journal of Astronomy and Astrophysics 2006年第2期6卷 155-164页

作者： Lei Sun Meng Su zu-hui fan Department of Astronomy Peking University Beijing 100871

We consider using future redshift surveys with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） to constrain the equation of state of dark energy w. We analyze the Alcock ＆ Paczynski （AP） effect imprinted on the two-point correlation function of galaxies in redshift space. The Fisher matrix analysis is applied to estimate the expected error bounds of w0 and wα from galaxy redshift surveys, w0 and wα being the two parameters in the equation of state parametrization w（z） = w0 ＋ wαz/（1 ＋ z）. Strong degeneracies between w0 and wα are found. The direction of the degeneracy in w0 - wα plane, however, rotates counter-clockwise as the redshift increases. LAMOST can potentially contribute in the redshift range up to 0.5. In combination with other high redshift surveys, such as the proposed Kilo-Aperture Optical Spectrograph project （KAOS）, the joint constraint derived from galaxy surveys at different redshift ranges is likely to efficiently break the degeneracy of w0 and wα. We do not anticipate that the nature of dark energy can be well constrained with LAMOST alone, but it may help to reduce the error bounds expected from other observations, such as the Supernova/Acceleration Probe （SNAP）.

关键词： Cosmology: theory - galaxies: distances and redshifts - galaxy clustering - large-scale structure of Universe

Comparison of halo detection from noisy weak lensing convergence maps with Gaussian smoothing and MRLens treatment

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Research in Astronomy and Astrophysics 2011年第5期11卷 507-523页

作者： Yang-XiuJiaoj Huan-YuanShan zu-huifan DepartmentofAstronomy PekingUniversityBeijing100871China

Taking into account the noise from intrinsic ellipticities of source galaxies, we study the efficiency and completeness of halo detections from weak lensing convergence maps. Particularly, with numerical simulations, we compare the Gaussian filter with the so called MRLens treatment based on the modification of the Maximum Entropy Method. For a pure noise field without lensing signals, a Gaussian smoothing results in a residual noise field that is approximately Gaussian in terms of statistics if a large enough number of galaxies are included in the smoothing window. On the other hand, the noise field after the MRLens treatment is significantly non-Gaussian, resuiting in complications in characterizing the noise effects. Considering weak-lensing cluster detections, although the MRLens treatment effectively deletes false peaks arising from noise, it removes the real peaks heavily due to its inability to distinguish real signals with relatively low amplitudes from noise in its restoration process. The higher the noise level is, the larger the removal effects are for the real peaks. For a survey with a source density ng-30 arcmin^-2, the number of peaks found in an area of 3 x 3 deg2 after MRLens filtering is only-50 for the detection threshold n = 0.02, while the number of halos with M 〉 5 x 1013 Me and with redshift z 〈 2 in the same area is expected to be-530. For the Gaussian smoothing treatment, the number of detections is-260, much larger than that of the MRLens. The Gaussianity of the noise statistics in the Gaussian smoothing case adds further advantages for this method to circumvent the problem of the relatively low efficiency in weak-lensing cluster detections. Therefore, in studies aiming to construct large cluster samples from weak-lensing surveys, the Gaussian smoothing method performs significantly better than the MRLens treatment.

关键词： cosmology: theory-gravitation-dark matter-gravitational lensing

Role of texture before rolling: a research based on texture and magnetic properties of 4.5 wt.% Si non-oriented electrical steel

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Journal of Iron and Steel Research International 2024年第8期31卷 1973-1986页

作者： Yu-fan Wang Guo-qing zu Shi-cheng Sun Ying Han Wei-wei Zhu hui Wu Yu Zhao Xu Ran Key Laboratory of Advanced Structural Materials of Ministry of Education Changchun University of TechnologyChangchun 130012JilinChina CRRC Changchun Railway Vehicles Co. Ltd.Changchun 130000JilinChina School of Metallurgy Northeastern UniversityShenyang 110819LiaoningChina School of Mechanical MaterialsMechatronic and Biomedical EngineeringUniversity of WollongongWollongongNSW 2522Australia

The evolution of microstructure,texture,and magnetic properties with random texture,near-copper texture,weak near-cube texture,and strong λ fiber(/ND(normal direction))before rolling of non-oriented electrical steel was *** recrystallized hot bands with different textures but similar grain sizes were prepared by pre-annealing at low-temperature and high-temperature normalization *** was observed that the final annealed products exhibited similar recrystallized *** contrast,the final annealed product with more 2 fiber before rolling exhibited a stronger cube *** the fiber before rolling becoming stronger,the proportion of(111)deformed matrices became larger,which could be observed in the early recrystallization *** overwhelmingly dominant 2 orientation nuclei are formed in the(111)deformed matrix and become the dominant ***,the best magnetic properties are obtained in the products with strong 2 fiber before rolling,corresponding to the strong cube texture and low anisotropyparameter.

关键词： Texture before rolling Non-oriented electrical steel-Nucleation Grain growth Magnetic property

Tumor microenvironment reprogramming by nanomedicine to enhance the effect of tumor immunotherapy

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Asian Journal of Pharmaceutical Sciences 2024年第2期19卷 1-37页

作者： Yu Huang hui fan huihui Ti School of Chinese Materia Medica Guangdong Pharmaceutical UniversityGuangzhou 510006China Guangdong Province Precise Medicine Big Date of Traditional Chinese Medicine Engineering Technology Research Center Guangdong Pharmaceutical UniversityGuangzhou 510006China School of Pharmacy Guangdong Pharmaceutical UniversityGuangzhou 510006China

With the rapid development of the fields of tumor biology and immunology, tumor immunotherapy has been used in clinical practice and has demonstrated significant therapeutic potential, particularly for treating tumors that do not respond to standard treatment options. Despite its advances, immunotherapy still has limitations, such as poor clinical response rates and differences in individual patient responses, largely because tumor tissues have strong immunosuppressive microenvironments. Many tumors have a tumor microenvironment (TME) that is characterized by hypoxia, low pH, and substantial numbers of immunosuppressive cells, and these are the main factors limiting the efficacy of antitumor immunotherapy. The TME is crucial to the occurrence, growth, and metastasis of tumors. Therefore, numerous studies have been devoted to improving the effects of immunotherapy by remodeling the TME. Effective regulation of the TME and reversal of immunosuppressive conditions are effective strategies for improving tumor immunotherapy. The use of multidrug combinations to improve the TME is an efficient way to enhance antitumor immune efficacy. However, the inability to effectively target drugs decreases therapeutic effects and causes toxic side effects. Nanodrug delivery carriers have the advantageous ability to enhance drug bioavailability and improve drug targeting. Importantly, they can also regulate the TME and deliver large or small therapeutic molecules to decrease the inhibitory effect of the TME on immune cells. Therefore, nanomedicine has great potential for reprogramming immunosuppressive microenvironments and represents a new immunotherapeutic strategy. Therefore, this article reviews strategies for improving the TME and summarizes research on synergistic nanomedicine approaches that enhance the efficacy of tumor immunotherapy.

关键词： Tumor immunotherapy Tumor micr oenvir onment Nanomedicine Tumor repr ogramming

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

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China Communications 2024年第4期21卷 38-52页

作者： Jiang fan Qin Junwei Liu Lei Tian hui School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy co

关键词： associative tasks cache-aided procedure double deep Q-network Internet of Medical Things(IoMT) multi-access edge computing(MEC)

A hybrid WUDT-NAFnet for simultaneous source data deblending

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Petroleum Science 2024年第3期21卷 1649-1659页

作者： Chao-fan Ke Shao-Huan zu Jun-Xing Cao Xu-Dong Jiang Chao Li Xing-Ye Liu Key Laboratory of Earth Exploration and Information Technology of Ministry of Education Chengdu University of Technology State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of Technology College of Geophysics Chengdu University of Technology

Simultaneous source technology,which reduces seismic survey time and improves the quality of seismic data by firing more than one source with a narrow time interval,is compromised by the massive blended ***,deblending algorithms have been developed to separate this ***,deep learning(DL)has been proved its great potential in suppressing the *** most popular DL method employs neural network as a filter to attenuate the blended noise in an iterative estimation and subtraction framework(IESF).However,there are still amplitude distortion and blended noise residual problems,especially when dealing with weak signal submerged in strong *** address these problems,we propose a hybrid WUDT-NAFnet,which contains two *** first network is a wavelet based U-shape deblending transformer network(WUDTnet),incorporated into IESF as a robust regularization term to iteratively separate the blended *** second network is a nonlinear activate free network(NAFnet)designed to recover the event amplitude and further suppress the weak noise residual in *** the hybrid network,the blended noise can be separated purposefully and *** using synthetic and field seismic data demonstrate that the WUDTNAFnet outperforms traditional curvelet transform(CT)based method and the deblending transformer(DT)model in terms of ***,for field applications,the data augmentation method of bicubic interpolation is applied to mitigate the feature difference between synthetic and field ***,the trained network exhibits strong signal preservation ability in numerical field example without requiring additional training.

关键词： Simultaneous-source Deblending Deep learning Transformer

Data complexity-based batch sanitization method against poison in distributed learning

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Digital Communications and Networks 2024年第2期10卷 416-428页

作者： Silv Wang Kai fan Kuan Zhang hui Li Yintang Yang State Key Laboratory of Integrated Service Networks Xidian UniversityXi'an710126China Department of Electrical and Computer Engineering University of Nebraska-LincolnLincolnNE68588USA Key Lab.of the Minist.of Educ.for Wide Bandgap Semiconductor Materials and Devices Xidian UniversityXi'an710071China

The security of Federated Learning(FL)/Distributed Machine Learning(DML)is gravely threatened by data poisoning attacks,which destroy the usability of the model by contaminating training samples,so such attacks are called causative availability indiscriminate *** the problem that existing data sanitization methods are hard to apply to real-time applications due to their tedious process and heavy computations,we propose a new supervised batch detection method for poison,which can fleetly sanitize the training dataset before the local model *** design a training dataset generation method that helps to enhance accuracy and uses data complexity features to train a detection model,which will be used in an efficient batch hierarchical detection *** model stockpiles knowledge about poison,which can be expanded by retraining to adapt to new *** neither attack-specific nor scenario-specific,our method is applicable to FL/DML or other online or offline scenarios.

关键词： Distributed machine learning security Federated learning Data poisoning attacks Data sanitization Batch detection Data complexity

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu hui Zeng Bin fan the School of Intelligence Science and Technology and the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

Probing primordial gravitational waves: Ali CMB Polarization Telescope

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National Science Review 2019年第1期6卷 145-154页

作者： Hong Li Si-Yu Li Yang Liu Yong-Ping Li Yifu Cai Mingzhe Li Gong-Bo Zhao Cong-Zhan Liu Zheng-Wei Li He Xu Di Wu Yong-Jie Zhang zu-hui fan Yong-Qiang Yao Chao-Lin Kuo fang-Jun Lu Xinmin Zhang Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Theoretical Physics Division Institute of High Energy PhysicsChinese Academy of Sciences University of Chinese Academy of Sciences CAS Key Laboratory for Researches in Galaxies and Cosmology Department of AstronomyUniversity of Scienceand Technology of China Interdisciplinary Center for Theoretical Study University of Science and Technology of China National Astronomical Observatories Chinese Academy of Sciences Institute of Cosmology& Gravitation University of Portsmouth Key Laboratory of Particle Astrophysics Institute of High EnergyPhysics Chinese Academy of Sciences Key Laboratory of Particle Astrophysics Institute of High Energy Physics ChineseAcademy of Sciences Department of Astronomy School of Physics Peking University Physics Department Stanford University

In this paper, we will give a general introduction to the Ali CMB Polarization Telescope(Ali CPT) project,which is a Sino–US joint project led by the Institute of High Energy Physics and involves many different institutes in China. It is the first ground-based Cosmic Microwave Background(CMB) polarization experiment in China and an integral part of China’s Gravitational-wave Program. The main scientific goal of the Ali CPT project is to probe the primordial gravitational waves(PGWs) originating from the very early Universe. The AliCPT project includes two stages. The first stage, referred to as AliCPT-1, is to build a telescope in the Ali region of Tibet at an altitude of 5250 meters. Once completed, it will be the highest ground-based CMB observatory in the world and will open a new window for probing PGWs in the northern hemisphere. The AliCPT-1 telescope is designed to have about 7000 transition-edge sensor detectors at 95 GHz and 150 GHz. The second stage is to have a more sensitive telescope(Ali CPT-2) with more than 20 000 detectors. Our simulations show that AliCPT will improve the current constraint on the tensor-to-scalar ratio r by one order of magnitude with three years’ observation. Besides the PGWs, Ali CPT will also enable a precise measurement of the CMB rotation angle and provide a precise test of the CPT symmetry. We show that three years’ observation will improve the current limit by two orders of magnitude.

关键词： primordial gravitational waves cosmic microwave background Ali CMB Polarization Telescope